Essay
Culture
7 min read

Praying with Jane Austen

From Elizabeth Bennet to Emma, Jane Austen’s heroines often consider their own character then change. As the anniversary of the novelist’s birth approaches, Beatrice Scudeler explores their author's prayers.

Beatrice writes on literature, religion, the arts, and the family. Her published work can be found here

A head and shoulders portrait of a young woman inclining her gaze to one side.
Portrait of a Young Woman in White, 1798, Jacques-Louis David.

In his essay ‘A Note on Jane Austen’, C. S. Lewis argues that the heroines in each major Austen novel go through a process which he terms ‘undeception’, leading them to ‘discover that they have been making mistakes both about themselves and about the world in which they live.’ This can take the form of self-analysis, or of a more explicitly Christian examination of conscience. Elizabeth Bennet or Catherine Moreland may not be constantly described praying, for instance, but they certainly engage in a healthy amount of self-examination. On the other hand, we have a much more explicitly Christian example of repentance in the character of Marianne Dashwood in Sense and Sensibility, who, after her abandonment by Mr. Willoughby, and having just recovered from a dangerous illness, confesses to her sister that is grateful to have been given the chance to repent and ‘have time for atonement to my God.’ But what about Austen herself? What was the role of self-examination in her own life?  

I got my answer earlier this year, when my husband and I went on a Jane Austen prayer retreat at the charming vicarage of Edenham, Lincolnshire. When not engaged in prayer, we spent our time learning about and discussing Austen’s faith, which she practised devoutly throughout her life as the daughter of an Anglican clergyman. Austen’s life was immersed in prayer.  

According to Fr. Ed Martin, who hosted the retreat, the Austens would have read through all of the Old Testament once in a year, the New Testament twice in a year, and the Psalms once each month. What’s more, Fr. Ed estimated that, once personal devotion and church services were accounted for, Austen would have prayed the Lord’s prayer about 30,000 times over her the course of her life. 

I was also delighted to learn more about one of only twenty books that we know with certainty to have been in Austen’s personal collection – A Companion to the Altar by William Vickers. Austen’s copy, signed 1794, resides at the Princeton University Library; according to Irene Collins, whose book Jane Austen: The Parson’s Daughter (1998) I highly recommend, Austen made regular use of Vickers’ book, which was meant as a guide for Anglicans to prepare themselves spiritually to receive Holy Communion.  

I was intrigued to read A Companion to the Altar for myself. What stood out to me is Vickers’ emphasis on self-examination and repentance as crucial to one’s spiritual life, especially leading up to Sundays when a communion service was going to happen. This struck me as being very much in keeping with the experience of the heroines in Austen’s novels which Lewis details in his essay on Austen. 

These three prayers also reveal that, for Austen, the key to a virtuous life resides not in blindly sticking to a set of moral rules, but rather in cultivating one’s character. 

While thinking about these ideas of examination of conscience and repentance, I was reminded that, thanks to her sister Cassandra, three of Jane Austen’s own prayers have survived. They were penned by Austen as an adult, judging by the handwriting, and would have been written for the purpose of personal or family devotion, especially on a Sunday evening. These three prayers, though brief, reflect – and even clarify – so many of the issues that Austen returns to again and again in her novels: the danger of pride, the necessity of repentance and humility, and more generally, a call to lead a virtuous life. For example, in the third prayer she writes: 

Incline us oh God! to think humbly of ourselves, to be severe only in the examination of our own conduct, to consider our fellow-creatures with kindness, and to judge all they say and do with that charity which we would desire from them ourselves. 

This passage could have been written for Emma Woodhouse herself! After the disastrous trip to Box Hill, where she deeply embarrasses Miss Bates in front of their friends, we are told that the normally confident and even haughty Emma admits that ‘She had often been remiss, her conscience told her so’ and, after much reflection, she experiences ‘the warmth of true contrition.’ Nor does this call to humility apply solely to Austen’s female characters.  

While Lewis does not extend his concept of ‘undeception’ to Austen’s heroes, this is clearly what happens to Mr. Darcy by the end of Pride and Prejudice, so much so that, once he has realised the extent of his past pride, he tells Elizabeth, ‘By you, I was properly humbled.’ Similarly, in Persuasion Captain Wentworth admits to Anne Elliot that if he had not been ‘too proud’, their separation need not have been so long, and they might have been able to get married and begin a life together much sooner.  

These three prayers also reveal that, for Austen, the key to a virtuous life resides not in blindly sticking to a set of moral rules, but rather in cultivating one’s character, starting by training one’s disposition through habitual practice of certain key virtues like charity, patience, and humility. As Alasdair Macintyre notes in his seminal philosophical work After Virtue (1981), Jane Austen follows ancient philosopher Aristotle in thinking that ‘Virtues are dispositions not only to act in particular ways, but also to feel in particular ways.’ Therefore, a moral education is not simply about doing what’s right whether you feel like it or not. Rather, it’s an ‘education sentimentale’: it’s about becoming morally mature enough to do the right thing not because you have to, but because you want to. Let me quote here a key passage from the first surviving prayer, in which Austen is asking God for forgiveness and guidance: 

Look with Mercy on the Sins we have this day committed, and in Mercy make us feel them deeply, that our Repentance may be sincere, & our resolutions steadfast of endeavouring against the commission of such in future. Teach us to understand the sinfulness of our own Hearts, and bring to our knowledge every fault of Temper and every evil Habit in which we have indulged to the discomfort of our fellow-creatures, and the danger of our own Souls. May we now, and on each return of night, consider how the past day has been spent by us, what have been our prevailing Thoughts, Words, and Actions during it, and how far we can acquit ourselves of Evil. Have we thought irreverently of Thee, have we disobeyed thy commandments, have we neglected any known duty, or willingly given pain to any human being? Incline us to ask our Hearts these questions Oh! God, and save us from deceiving ourselves by Pride or Vanity. 

Everything about Austen’s petitions to God in this prayer revolves around the formation of a virtuous character. First of all, she wishes that her ‘repentance’ may be ‘sincere’, and her ‘resolutions’ to lead a more virtuous life ‘steadfast.’ But how are we to achieve such sincere repentance? For Austen, it is through the examination of our disposition. She invites God to bring to her knowledge ‘every fault of Temper and every evil Habit’ in which she has ‘indulged’. As you can see, the focus here is not on resolving never to do one specific ‘bad’ thing again; rather, it is on getting rid of bad habits, so that you will not even be tempted to do that bad thing in the future. This becomes even clearer in the final section I quoted: ‘Incline us to ask our Hearts these questions Oh! God, and save us from deceiving ourselves by Pride or Vanity.’ Achieving virtue is a matter of a sentimental education, in the sense of having the right feelings; for Austen, a devout Christian, this can only happen with God’s aid. Both Lewis and Macintyre, then, got it right. Lewis is right that Jane Austen is deeply concerned with the fictions which we tell ourselves, and which lead us away from goodness. She asks God to save her from ‘deceiving’ herself by ‘Pride’ and, like Lewis shows, whenever one of her heroines falls precisely into this trap, a process of ‘undeception’ always takes place. But Macintyre is also right in pointing out that undeception cannot take place until we train our ‘Hearts’, not just our heads, into a habit of virtue.  

What both Macintyre and Lewis guessed from Austen’s novels, we can experience and understand more directly by reading Austen’s prayers. We learn from her direct addresses to God how seriously she took the sin of pride, and how highly the virtue of humility ranked for her. We learn that no true repentance can happen without regular self-examination and confidence in God’s forgiveness. We learn that true virtue can only be gained through habit, and that constancy in practising virtues like humility and charity is crucial, even in the face of our own mistakes. If you are already someone of faith, I urge you to read Austen’s prayers and make use of them in your prayer life. If you don’t consider yourself a Christian, I urge you to read her prayers nonetheless: you may find they help you on your way to the kind of self-examination, without which none of Austen’s heroes or heroines could have achieved happiness. 

Article
AI - Artificial Intelligence
Culture
10 min read

We’ll learn to live with AI: here’s how

AI might just help us with life’s dilemmas, if we are responsible.

Andrew is Emeritus Professor of Nanomaterials at the University of Oxford. 

Two construction workers stand and talk with a humanoid AI colleague.
Nick Jones/Midjourney.ai

Anxiety about algorithms is nothing new.  Back in 2020, It was a bad summer for the public image of algorithms. ‘I am afraid your grades were almost derailed by a mutant algorithm’, the then Prime Minister told pupils at a school. No topic in higher education is more sensitive than who gets a place at which university, and the thought that unfair decisions might be based on an errant algorithm caused understandable consternation. That algorithms have been used for many decades with widespread acceptance for coping with examination issues ranging from individual ill health to study of the wrong set text by a whole school seems quietly to have slipped under the radar.  

Algorithmic decision-making is not new. Go back thousands of years to Hebrew Deuteronomic law: if a man had sex with a woman who was engaged to be married to another man, then this was unconditionally a capital offence for the man. But for the woman it depended on the circumstances. If it occurred in a city, then she would be regarded as culpable, on the grounds that she should have screamed for help. But if it occurred in the open country, then she was presumed innocent, since however loudly she might have cried out there would have been no one to hear her. This is a kind of algorithmic justice: IF in city THEN woman guilty ELSE woman not guilty.  

Artificial intelligence is undergoing a transition from classification to decision-making. Broad artificial intelligence, or artificial general intelligence (AGI), in which the machines set their own goals, is the subject of gripping movies and philosophical analysis. Experts disagree about whether or when AGI will be achieved. Narrow artificial intelligence (AI) is with us now, in the form of machine learning. Where previously computers were programmed to perform a task, now they are programmed to learn to perform a task.  

We use machine learning in my laboratory in Oxford. We undertake research on solid state devices for quantum technologies such as quantum computing. We cool a device to 1/50 of a degree above absolute zero, which is colder than anywhere in the universe that we know of outside a laboratory, and put one electron into each region, which may be only 1/1000 the diameter of a hair on your head. We then have to tune up the very delicate quantum states. Even for an experienced researcher this can take several hours. Our ‘machine’ has learned how to tune our quantum devices in less than 10 minutes.  

Students in the laboratory are now very reluctant to tune devices by hand. It is as if all your life you have been washing your shirts in the bathtub with a bar of soap. It may be tedious, but it is the only way to get your shirts clean, and you do it as cheerfully as you can … until one day you acquire a washing machine, so that all you have to do is put in the shirts and some detergent, shut the door and press the switch. You come back two hours later, and your shirts are clean. You never want to go back to washing them in the bathtub with a bar of soap. And no one wants to go back to doing experiments without the machine. In my laboratory the machine decides what the next measurement will be.  

Suppose that a machine came to know my preferences better than I can articulate them myself. The best professionals can already do this in their areas of expertise, and good friends sometimes seem to know us better than we know ourselves. 

Many tasks previously reserved for humans are now done by machine learning. Passport control at international airports uses machine learning for passport recognition. An experienced immigration officer who examines one passport per minute might have seen four million faces by the end of their career. The machines were trained on fifty million faces before they were put into service. No wonder they do well.  

Extraordinary benefits are being seen in health care. There is now a growing number of diagnostic studies in which the machines outperform humans, for example, in screening ultrasound scans or radiographs. Which would you rather be diagnosed by? An established human radiologist, or a machine with demonstrated superior performance? To put it another way, would you want to be diagnosed by a machine that knew less than your doctor? Answer: ‘No!’ Well then, would you want to be diagnosed by a doctor who knew less than the machine? That’s more difficult. Perhaps the question needs to be changed. Would you prefer to be treated by a doctor without machine learning or by a doctor making wise use of machine learning?  

If we want humans to be involved in decisions involving our health, how much more in decisions involving our liberty. But are humans completely reliable and consistent? A peer-reviewed study suggested that the probability of a favourable parole decision depended on whether the judges had had their lunch. The very fact that appeals are sometimes successful provides empirical evidence that law, like any other human endeavour, involves uncertainty and fallibility. When it became apparent that in the UK there was inconsistency in sentencing for similar offences, in what the press called a postcode lottery, the Sentencing Council for England and Wales was established to promote greater transparency and consistency in sentencing. The code sets out factors which judges must consider in passing sentence, and ranges of tariffs for different kinds of crimes. If you like, it is another step in algorithmic sentencing. Would you want a machine that is less consistent than a judge to pass sentence? See the sequence of questions above about a doctor.  

We may consider that judicial sentencing has a special case for human involvement because it involves restricting an individual’s freedom. What about democracy? How should citizens decide how to vote when given the opportunity?  Voter A may prioritise public services, and she may seek to identify the party (if the choices are between well identified parties) which will best promote education, health, law and order, and other services which she values. She may also have a concern for the poor and favour redistributive taxation. Voter B may have different priorities and seek simply to vote for the party which in his judgement will leave him best off. Other factors may come into play, such as the perceived trustworthiness of an individual candidate, or their ability to evoke empathy from fellow citizens.  

This kind of dilemma is something machines can help with, because they are good at multi-objective optimisation. A semiconductor industry might want chips that are as small as possible, and as fast as possible, and consume as little power as possible, and are as reliable as possible, and as cheap to manufacture as possible, but these requirements are in tension with one another. Techniques are becoming available to enable machines to make optimal decisions in such situations, and they may be better at them than humans. Suppose that a machine came to know my preferences better than I can articulate them myself. The best professionals can already do this in their areas of expertise, and good friends sometimes seem to know us better than we know ourselves. Suppose also that the machine was better than me at analysing which candidate if elected would be more likely to deliver the optimal combination of my preferences. Might there be something to be said for benefitting from that guidance?  

If we get it right, the technologies of the machine learning age will provide new opportunities for Homo fidelis to promote human flourishing at its best.

By this point you may be sucking air through your intellectual teeth. You may be increasingly alarmed about machines taking decisions that should be reserved for humans. What are the sources of such unease? One may be that, at least in deep neural networks, the decisions that machines make may be only as good as the data on which they have been trained. If a machine has learned from data in which black people have an above average rate of recidivism, then black people may be disadvantaged in parole decisions taken by the machine. But this is not an area in which humans are perfect; that is why we have hidden bias training. In the era of Black Lives Matter we scarcely need reminding that humans are not immune to prejudice.  

Another source of unease may be the use to which machine learning is put for commercial and political ends. If you think that machine learning is not already being applied to you, you are probably mistaken. Almost every time you do an online search or use social media, the big data companies are harvesting your data exhaust for their own ends. Even if your phone calls and emails are secure, they still generate metadata. European legislation is better than most, and the Online Safety Act 2023 will make the use of Internet services safer for individuals in the United Kingdom. But there is a limit to what regulation can protect, and 2024 is likely to see machine learning powerfully deployed to sway voters in elections in half the world. Targeted persuasion predates AI, as Othello’s Iago knew, but machine learning has brought it to an unprecedented level of industrialisation, with some of the best minds in the world paid some of the highest salaries in the world to maximise the user’s screen time and the personalisation of commercial and political influence.  

Need it be so? In some ways advances in machine learning are acting as the canary in the mine, alerting us to fundamental questions about what humans are for, and what it means to be human. The old model of Homo economicus—rational, selfish, greedy, lazy man—has passed its sell-by date. It is being replaced by what I like to call Homo fidelis—ethical, caring, generous, energetic woman and man. For as long as AGI remains science fiction, it is up to humans to determine what values the machines are to implement. If we get it right, the technologies of the machine learning age will provide new opportunities for Homo fidelis to promote human flourishing at its best.  

Whatever the future capabilities of machines, they cannot be morally load-bearing because humans are self-aware and mortal, whereas machines are not.

Paul Collier and John Kay

Christians have been thinking about what it means to be human for two millennia, building on what came before, and so they ought to have something to contribute to how humans flourish. In It Keeps Me Seeking, my co-authors and I ask our readers to imagine that they were writing about three thousand years ago for people who knew nothing of modern genetics or psychological science about what it means to be human. ‘You are writing for a storytelling culture, and so you would probably put it in the form of a story. Let’s say you set it in a garden. The garden is pleasant, but it is also designed for character formation, and so there is work to do, and also the possibility for a hard moral choice. You want to convey that humans need social interactions (for the same reason that solitary confinement is a severe punishment), and so you try the literary thought experiment of having one solitary man and letting him encounter animals and name them. Animals can be useful and they can be good company. But ultimately no animals, not even a dog, are fully satisfactory as partners in work and companions in life. Humans need humans. An enriching component of human relationships is sex. So, the supreme gift to the solitary man in our story is companionship with an equal who is both like and unlike; a woman. It is hardly a complete account, but it is a good start. Oh, and there is one other aspect. They should be free of the shame which lies at the root of so much psychological disorder.’  

As far as it goes, would you regard such an account as complete? If not, what would you add next? You can see where this is going. To be human you need to be responsible. So, you let the humans face the moral choice. You can even include an element of disinformation to make the choice harder. And then when it goes horribly wrong you let them discover that they are responsible for their actions, and that blaming one another does not help. If you have God in your story, then (uniquely for the humans) responsibility consists of accountability to God. This is how human distinctiveness was addressed in early Jewish thought. As an early articulation that to be human means to be responsible, the story of Adam and Eve is unsurpassed.  

In Greed is Dead, Paul Collier and John Kay reference Citizenship in a Networked Age as brilliantly elucidating the issue of morally pertinent decision-taking. They write, ‘Whatever the future capabilities of machines, they cannot be morally load-bearing because humans are self-aware and mortal, whereas machines are not. Machines can be used not only to complement and enhance human decision-making, but for bad: search optimisation has already morphed into influence-optimisation. We must keep morally pertinent decision-taking firmly in the domain of humanity.’  

The nature of humanity includes responsibility—for wise use of machine learning and much more besides. Accountability is part of life for people with widely differing philosophical, ethical, and religious world views. If we are willing to concede that accountability follows responsibility, then we should next ask, ‘Accountable to whom?’